Who Moved My Intelligence?
The title of this article is inspired by a self-help book from the 1990’s called ‘Who moved my Cheese: An Amazing Way to Deal with Change in Your Work and in Your Life’. Despite significant criticism, this book became a best seller and a popular tool in any change manager’s back pocket. The implications of Artificial Intelligence (AI) and automation for change in the future workplace is the subject of much current debate. But how should educators respond? How can they ensure that they benefit from AI?
Re-imagining teaching and schooling
AI refers to the capabilities of computers to perform intelligent behaviours that we would think of as essentially human. Most readers will be familiar with a practical application of AI, the sort of technology we use to navigate information on the internet, find our way around our environment or enter a country with our e-Passport. But what does the increased popularity and the increasing sophistication of AI technology mean for education?
To answer this question, I focus on two interpretations of the question: ‘Who moved my Intelligence?’. Interpretation 1 considers how we need to ‘move’ our students’ intelligence beyond the routine cognitive processing of academic subject matter. Interpretation 2 will consider what ‘moving’ certain intelligent workplace behaviours from human performance to AI performance means for educators, including for the job of teaching.
Developing the uniquely human abilities of students
Education and training organizations need to review what and how they teach to ensure that AI is designed and used as a tool to make our students and trainees smarter. We do not want AI to be used as a technology that takes over human roles in a way that ‘dumbs us down.’ We therefore need to concentrate on designing and implementing teaching and schooling that develops the uniquely human abilities of our students and instills within them the requisite subject knowledge in a flexible, interdisciplinary and accessible manner.
The human capability for Metacognition, both in terms of self-understanding so that each of us has an accurate knowledge of what we do and do not understand; and self-regulation so that we can all plan and monitor our learning effectively, will be at a premium in the future workplace. This is because metacognition is not something that AI can achieve, and because we will all need to be lifelong learners flexibly developing our knowledge and skills to meet the demands of the future, we will all therefore need to develop better metacognitive skills.
The use of teaching approaches such as Collaborative Problem Solving (CPS) will become more essential. CPS has been shown to have the potential to provide learners with an understanding of key subject knowledge synthesized across disciplines that they can apply in a flexible manner to real world problems. Collaboration and problem solving are also among the key 21st century skills demanded in the modern workplace, because routine cognitive skills and knowledge are easy to automate with AI.
The curriculum will also need to include AI as a subject, not merely to teach a small sub set of the population to design and build AI systems, but to teach the whole population what AI is and what it can and cannot do. Everyone needs to understand enough about AI to be able to use it effectively in their lives at work and at home, to be able to contribute to important decisions about what is and is not ethical and permissible for an AI to do, and to be able to make decisions about the division of labour between artificial and human intelligences.
There is no doubt that there will be a shift in the distribution of intelligence within the workplace, including classrooms and schools. In order to extract the most benefit from this redistribution, we need to ensure that the most automation-appropriate activities are done by the AI, and likewise that the most human-appropriate activities are done by people.
Re-imagine teaching and schooling with AI assistants to provide intelligent analysis of multiple data sources about learners, from sleep sensors, library usage and e-learning resource interactions, to social media activity. This analysis will illustrate how learning is progressing to support ongoing detailed formative assessment. AI assistants could also relieve teachers from the routine automatable parts of their job, and enable teachers to focus on human sensitive support and communication.